Outside the Box Ways to Show Members Your Appreciation
Bibliographic record
Abstract
What are some creative ways in which you showed appreciation for members? “For our select, highest-tier members, we created a lounge at our annual meeting where they can relax and recharge for the meeting. Additionally, we invite those members to special events during the annual meeting such as wine tasting or horseback riding.” — Amanda Plummer, CAE, Associate Director, Legal and Human Resources, Society of Critical Care Medicine, Mount Prospect, IL. Phone (847) 827-6888. Email: [email protected]. Website: sccm.org “Aside from taking time to share personalized digital spotlights of members and tailored videos that thank and recognize the impact of members, I've found authentic outreach to be very effective. Whether it's an email exchange with a member or a hello and a quick chat at a members' event, taking time for interaction with members is a simple but powerful way to convey how much they're valued.” — Edward Byers, Founder, CANRev Collaborative, Toronto, Ontario, Canada. Phone (416) 737-7424. Email: [email protected]. Website: canrevcollab.com
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".